Where Economics and Philosophy Meet: Review of the Elgar Companion to Economics and Philosophy with Responses from the Authors
Bibliographic record
Abstract
Although Adam Smith’s 1776 Wealth of Nations is often cited as marking the birth of economics, it was really not until after the second world war that economics became the distinctive, more or less unified, and largely separate discipline summarised in the textbooks of today. Even a mere fifty years ago, it was possible for the intelligent reader to move with relative ease between economics on the one hand and political economy, sociology and social theory, psychology and philosophy on the other. This is now no longer the case, and most young economists are taught to think of their discipline, not primarily in terms of the particular ‘economic’ social phenomena it was once taken to be about, but as a sophisticated and largely self‐contained analytical approach to the investigation of social phenomena of any kind. Even so, economics has never been able to separate itself entirely from its sister disciplines, even at the high tide of mathematical economics and positivism during the 1970s and 1980s, and many of the most active new areas in economics currently involve some form of boundary crossing (e.g. experimental economics, neuroeconomics and computational economics to name just three). With respect to the philosophy of economics in particular, the last fifty years or so have seen a steady expansion in scholarly investigation into different connections between economics and philosophy, with the emergence of new journals, professional associations, research networks and the like. There has been a great deal of work on epistemological questions in the wake of the decline of positivism, on boundary issues and the question of whether or not economics constitutes a science, and on the rhetoric of economics, ethics, value and, latterly, the ontology of economics (Hands, 2001).
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.011 | 0.016 |
| Science and technology studies | 0.003 | 0.008 |
| Scholarly communication | 0.008 | 0.011 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.007 | 0.013 |
| Insufficient payload (model declined to judge) | 0.010 | 0.006 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".